Control method based on artificial intelligence indication board and ice and snow tourism indication board

Abstract

The invention relates to the technical field of ice and snow tourism, and particularly discloses a control method based on an artificial intelligence indication board and an ice and snow tourism indication board, and the method comprises the steps: collecting environment data in real time through a sensor disposed on the indication board, and collecting tourism information in a preset range in real time through a wireless network technology; analyzing the real-time environment data by adopting an artificial intelligence algorithm, predicting an optimal route and a travel mode within a preset time period in combination with historical data, and generating a data analysis result; according to the invention, environmental data is collected in real time by using a deployed sensor, and tourism information in a preset range is collected in real time in combination with a wireless network technology; through combined analysis of environmental data and historical data by an artificial intelligence algorithm, an optimal route and a travel mode in a specific time period are predicted, so that accurate and personalized travel suggestions are provided; based on the analysis results, the indication board can automatically generate dynamic display content and update display information in real time.

Description

Technical Field

[0001] The present invention belongs to the technical field of ice and snow tourism, and particularly relates to a control method for an artificial intelligence-based sign and an ice and snow tourism sign. Background Art

[0002] Nowadays, more and more Chinese people are engaged in ice and snow sports, and ice and snow consumption in China shows a rapid expansion trend. With the gradual rise of ice and snow tourism, tourists' demands for navigation, route planning, weather information, etc. in ice and snow scenic spots are increasing day by day. Traditional signs and markings are difficult to meet the needs of tourists in complex and changeable natural environments.

[0003] The weather conditions in ice and snow tourism venues are relatively harsh, and safety accidents such as congestion and falls are likely to occur; and when receiving tourists, it is necessary to remind tourists to show civilized travel and not to damage ornamental landscapes such as snow sculptures and ice lanterns. At present, there are already some intelligent signs based on Internet of Things technology, but most of them are limited to basic information display and guidance of preset routes, and cannot be optimized and adjusted in real time according to dynamic factors such as weather, road conditions, and tourists' personalized needs. Existing manual signs and static markings are difficult to cope with complex natural environments and tourists' personalized needs. Especially in extreme weather such as cold and snowy weather, signs are easily damaged by snow accumulation or low temperature, and cannot be flexibly adjusted according to the real-time environment or tourists' needs. In existing technologies, most intelligent signs rely on fixed preset data, lack real-time dynamic analysis and adaptability, and cannot meet the complex and changeable conditions in ice and snow tourism. There is still a large room for improvement in the adaptability to this special environment of ice and snow tourism.

[0004] Therefore, it is necessary to propose a control method for an artificial intelligence-based sign and an ice and snow tourism sign to solve the problems in the existing technology that the information of signs is not updated in a timely manner in extreme environments and cannot be flexibly adjusted according to the real-time environment.

[0005] The above information disclosed in this background art is only used to increase the understanding of the background art of the present invention. Therefore, it may include prior art that is not known to ordinary technicians in this field. Summary of the Invention

[0006] The purpose of the present invention is to provide a control method for an artificial intelligence-based sign and an ice and snow tourism sign to solve the problems in the above background art that the information of signs is not updated in a timely manner in extreme environments and cannot be flexibly adjusted according to the real-time environment.

[0007] To achieve the above purpose, the present invention provides the following technical solutions:

[0008] A control method for an artificial intelligence-based sign, comprising:

[0009] Sensors deployed through signboards collect environmental data in real time and use wireless network technology to collect tourism information within a preset range in real time;

[0010] Use artificial intelligence algorithms to analyze the real-time environmental data, combine historical data to predict the best route and travel mode within a preset time period, and generate data analysis results;

[0011] Analyze the tourism information through NLP, generate decision-making information in combination with the data analysis results, and automatically generate dynamic display content based on the decision-making information;

[0012] Generate execution instructions based on the display content to control the signboard to display information, and automatically update the display content according to the new environmental data and tourism information.

[0013] Preferably, start the signboard system and perform self-check and initialization, obtain real-time weather information through the sensor, and obtain weather warning information from the interface of an external meteorological data source;

[0014] Obtain the location information of the signboard through GPS, and use a camera to obtain traffic flow and pedestrian density information in front of the signboard;

[0015] Use Kalman filtering to fuse different types of sensor data to obtain the fused sensor data. The Kalman filtering formula is as follows:

[0016] x′ k =x′ k-1 +K k (z k -Hx′ k-1 )

[0017] P k =(I-K k H)P k-1

[0018] K k =P k-1 H T (HP k-1 H T +R) -1

[0019] In the formula, x′ k is the state estimate at the current moment, x′ k-1 is the state estimate at the previous moment, K k is the Kalman gain, P k is the covariance matrix, P k-1 is the covariance matrix at the previous moment, I is the identity matrix, z kLet \(O\) be the observed value, \(H\) be the observation matrix, and \(R\) be the observation noise;

[0020] Use edge computing technology to perform real-time processing and preliminary analysis on the sensor data to obtain the environmental data;

[0021] Based on the position information of the signpost, use wireless network technology to collect the tourism information within a preset range in real time.

[0022] Preferably, use LSTM to analyze the environmental data and the historical data to capture the long-term dependencies between the environmental data;

[0023] Use a deep Q-network to analyze the environmental data, learn the long-term dependencies between the environmental data, and find the best route and travel mode within a preset time period;

[0024] According to the real-time environmental data, perform dynamic path optimization through the A* algorithm combined with the Dijkstra algorithm, and use the GA algorithm to adjust the best route and travel mode.

[0025] Preferably, use the SpaCy library to identify entity information related to tourism from the tourism information;

[0026] Based on the entity information, use BERT combined with sentiment analysis to extract context content from the tourism information and generate text with sentiment features;

[0027] Where \(g\) based on the output of BERT i represents the hidden state for each token and is used to determine the sentiment type of the tourism information:

[0028] SentimentScore = Softmax(W sent g i + b sent )

[0029] In the formula, \(W\) sent is the weight matrix for sentiment classification, \(b\) sent is the bias term, and the output Softmax value represents the probability of the sentiment category;

[0030] Combine the text with sentiment features and use a multi-objective optimization algorithm to optimize the best route and travel mode to generate travel suggestions;

[0031] According to the travel suggestions and combined with the data analysis results, generate multi-language decision information through NLP;

[0032] The integrated Tableau tool displays the decision-making information in the form of charts and maps to obtain the dynamic display content.

[0033] Preferably, the execution instruction is generated according to the display content using a rule-based decision engine, and the execution instruction is sent to the sign through the MQTT protocol;

[0034] The WebSocket technology is used to maintain a real-time connection with the sign and transmit the execution instruction and update content in real time;

[0035] Moreover, the generation and update of the display content can be remotely managed and updated in real time through a cloud server.

[0036] Preferably, the method also grabs the feedback information of tourists from an external system through the network, and docks with the tourism scenic area management platform in real time to obtain tourist flow, scenic spot scheduling, and emergency warning information, and supplements the tourism information after integration.

[0037] The ice and snow tourism sign includes:

[0038] An environment perception module for collecting environmental data and tourism information around the sign;

[0039] A data processing module for analyzing the environmental data and the tourism information using artificial intelligence algorithms, performing path planning and travel mode selection, and generating dynamic multilingual display content;

[0040] An information display module for displaying the dynamic display content;

[0041] A network communication module for performing data interaction with a cloud server and a tourism scenic area management platform to dynamically adjust the tourism information and the display content.

[0042] Preferably, the information display module is a high-brightness LED screen, which displays the display content through graphics and maps. The network communication module uses wireless communication technology to be seamlessly connected to the cloud server and the tourism scenic area management platform to achieve multi-party data sharing and real-time update.

[0043] Preferably, the sign adopts a design that is cold-resistant, snow-resistant, waterproof, and frost-resistant, and integrates an emergency help function to automatically contact the management personnel or the rescue team and provide the current location information and emergency situation of the tourists.

[0044] Compared with the prior art, the beneficial effects of the present invention are:

[0045] The present invention utilizes deployed sensors to collect environmental data in real time and combines wireless network technology to collect tourism information within a preset range in real time, ensuring the timeliness and comprehensiveness of information sources; through the combined analysis of environmental data and historical data by artificial intelligence algorithms, it predicts the best routes and travel modes within a specific time period, thereby providing accurate and personalized tourism recommendations; through NLP technology to analyze tourism information and generate decision-making information in combination with the data analysis results, ensuring the accuracy and practicality of the displayed content; most importantly, based on these analysis results, the sign can automatically generate dynamic display content and update the display information in real time to adapt to the changing environment and tourism needs.

[0046] The above summary is only for the purpose of the specification and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features of the present invention will be readily apparent by reference to the drawings and the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flowchart of a control method for an artificial intelligence-based sign of the present invention;

[0048] Figure 2 It is a framework diagram of an ice and snow tourism sign of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0049] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0050] Embodiment 1:

[0051] Please refer to Figure 1 As shown, a control method for an artificial intelligence-based sign includes:

[0052] Collect environmental data in real time through sensors deployed on the sign, and use wireless network technology to collect tourism information within a preset range in real time;

[0053] Adopt artificial intelligence algorithms to analyze the real-time environmental data, combine historical data to predict the best routes and travel modes within a preset time period, and generate data analysis results;

[0054] Analyze tourism information through NLP, generate decision-making information in combination with the data analysis results, and automatically generate dynamic display content based on the decision-making information;

[0055] Generate execution instructions based on the displayed content to control the sign for information display, and automatically update the displayed content according to the new environmental data and tourism information.

[0056] Start the sign system and perform self-check and initialization, obtain real-time weather information through sensors, and obtain weather warning information from the interface of external meteorological data sources;

[0057] Obtain the location information of the sign through GPS, and use the camera to obtain traffic flow and pedestrian density information in front of the sign;

[0058] Use Kalman filtering to fuse different types of sensor data to obtain fused sensor data. The Kalman filter formula is as follows:

[0059] x′ k =x′ k-1 +K k (z k -Hx′ k-1 )

[0060] P k =(I-K k H)P k-1

[0061] K k =P k-1 H T (HP k-1 H T +R) -1

[0062] In the formula, x′ k is the state estimate at the current moment, x′ k-1 is the state estimate at the previous moment, K k is the Kalman gain, P k is the covariance matrix, P k-1 is the covariance matrix at the previous moment, I is the identity matrix, z k is the observation value, H is the observation matrix, and R is the observation noise;

[0063] Use edge computing technology to perform real-time processing and preliminary analysis on sensor data to obtain environmental data;

[0064] Based on the location information of the sign, use wireless network technology to collect tourism information within a preset range in real time.

[0065] Use LSTM to analyze environmental data and historical data to capture the long-term dependencies between environmental data. The key formula is as follows:

[0066] f t =σ(W f ·[ht-1 , x t + b f )

[0067] i t = σ(W i · [h t-1 , x t + b i )

[0068] o t = σ(W o · [h t-1 , x t + b o )

[0069]

[0070] h t = o t · tanh(C t )

[0071] In the formula, f t , i t , o t are the forget gate, input gate, and output gate respectively. W f , W i , W o and W C are four weight matrices used to calculate the outputs of the four gates: the forget gate, input gate, output gate, and candidate cell state. is the candidate cell state, representing the combined result of the current input and the previous state. After being processed by the tanh activation function, C t is the cell state, b f , b i , b o and b C are four bias terms used to adjust the outputs of each gate and the candidate cell state. h t is the hidden state, σ is the sigmoid activation function, and tanh is the hyperbolic tangent activation function;

[0072] Use the deep Q-network to analyze environmental data, learn the long-term dependencies between environmental data, and find the best route and travel mode within a preset time period;

[0073] The deep Q-network selects the optimal travel mode by maximizing the Q-value function, which can be expressed as:

[0074]

[0075] In the formula, Q(s t , a t ) represents the value in state st Take action a below t The expected return, r t is the immediate reward, and γ is the discount factor.

[0076] According to the real-time environmental data, dynamic path optimization is carried out through the A* algorithm combined with the Dijkstra algorithm, and the GA algorithm is used to adjust the best route and travel mode.

[0077] The formula of the Dijkstra algorithm is:

[0078]

[0079] In the formula, d(v) is the shortest path distance from the starting point to vertex v, w(u, v) is the weight of edge u→v, and V is the set of all nodes.

[0080] Use the SpaCy library to identify tourism-related entity information from tourism information;

[0081] Based on the entity information, use BERT combined with sentiment analysis to extract context content from tourism information and generate text with sentiment features;

[0082] Among them, the output g based on BERT i represents the hidden state of each token and is used to determine the sentiment type of the tourism information:

[0083] SentimentScore = Softmax(W sent g i + b sent )

[0084] In the formula, W sent is the weight matrix for sentiment classification, b sent is the bias term, and the output Softmax value represents the probability of the sentiment category;

[0085] Combine the text with sentiment features to optimize the best route and travel mode through the multi-objective optimization algorithm and generate travel suggestions;

[0086] Multi-objective optimization objective function:

[0087] minα·f 1 (r) + β·f 2 (r) + γ·f 3 (r)

[0088] In the formula, f 1 (r), f 2 (r), f 3(r) represents different objective functions (e.g., time, distance, travel mode), α, β, and γ are weight coefficients, and r is a decision variable;

[0089] Generate multilingual decision-making information through NLP according to travel suggestions combined with data analysis results;

[0090] Integrate the Tableau tool to display decision-making information in the form of charts and maps, obtaining dynamic display content.

[0091] Generate execution instructions using a rule-based decision engine based on the display content, and send the execution instructions to the sign through the MQTT protocol;

[0092] Use WebSocket technology to maintain a real-time connection with the sign, and transmit execution instructions and updated content in real time;

[0093] Moreover, the generation and update of the display content can be remotely managed and updated in real time through the cloud server.

[0094] Grab the feedback information of tourists from external systems through the network, and dock with the tourism scenic area management platform in real time to obtain tourist flow, scenic spot scheduling, and emergency warning information, and integrate and supplement tourism information after integration.

[0095] Embodiment 2:

[0096] Please refer to Figure 2 As shown, the ice and snow tourism sign includes:

[0097] An environment perception module for collecting environmental data and tourism information around the sign;

[0098] A data processing module for analyzing environmental data and tourism information using artificial intelligence algorithms, performing path planning and travel mode selection, and generating dynamic multilingual display content;

[0099] An information display module for displaying dynamic display content;

[0100] A network communication module for data interaction with the cloud server and the tourism scenic area management platform to dynamically adjust tourism information and display content.

[0101] The information display module is a high-brightness LED screen, which displays display content through graphics and maps. The network communication module uses wireless communication technology to seamlessly connect with the cloud server and the tourism scenic area management platform to achieve multi-party data sharing and real-time update.

[0102] The sign adopts a cold-resistant, snow-resistant, waterproof, and anti-freezing design, and integrates an emergency help function to automatically contact the management personnel or the rescue team and provide the current location information and emergency situation of the tourists.

[0103]

[0104]

[0105] Example scenario:

[0106] Tourist Li is skiing at a ski resort:

[0107] Li checks the weather forecast for today through a smart sign. The sign shows that the temperature today is -3°C, light snow is expected, and some ski areas are temporarily closed due to snow accumulation. The sign recommends Ski Resorts A and B based on real-time data. The tourist flow at these two ski resorts is within the normal range and is less affected by snow accumulation. Li finally chooses to go to Ski Resort A.

[0108] On the way to Ski Resort A, the sign updates the route suggestions in real time based on real-time environmental data (such as snow volume, temperature changes) and traffic flow. If the tourist flow at Ski Resort A surges, the sign will automatically adjust to a ski resort with less people (such as Ski Resort B) to avoid congestion.

[0109] As can be seen from the above, the present invention uses deployed sensors to collect environmental data in real time, and combines wireless network technology to collect tourism information within a preset range in real time, ensuring the timeliness and comprehensiveness of information sources; through the combined analysis of environmental data and historical data by artificial intelligence algorithms, it predicts the best route and travel mode within a specific time period, so as to provide accurate and personalized tourism suggestions; through NLP technology to analyze tourism information, combined with the data analysis results to generate decision-making information, ensuring the accuracy and practicality of the display content; most importantly, based on these analysis results, the sign can automatically generate dynamic display content and update the display information in real time to adapt to the changing environment and tourism needs.

[0110] Embodiment 3:

[0111] The embodiment of the present invention also provides a computer-readable storage medium, on which a program of a control method of an artificial intelligence sign as described in any one of the above is stored. When the program is executed by a processor, it realizes each process of the control method embodiment and can achieve the same technical effect. To avoid repetition, it will not be elaborated here. Among them, the computer-readable storage medium, such as a read-only memory (Read-Only Memory, abbreviated as ROM), a random access memory (Random ACGess Memory, abbreviated as RAM), a magnetic disk or an optical disc, etc.

[0112] The implementation of this method and program enables the sign to remain flexible and timely updated in complex and extreme environments, greatly improving the accuracy and effectiveness of information display, enhancing the user experience, and avoiding the problem of slow response of traditional signs when dealing with environmental changes.

[0113] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0114] In the drawings of the disclosed embodiments of the present invention, only the structures related to the disclosed embodiments of the present invention are involved, and other structures can refer to the general design. Without conflict, the same embodiment and different embodiments of the present invention can be combined with each other.

[0115] The flowcharts shown in the drawings are only illustrative examples, not necessarily including all contents and operations / steps, nor necessarily executed in the described order. For example, some operations / steps can also be decomposed, combined, or partially merged, so the actual execution order may change according to the actual situation.

[0116] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A control method based on artificial intelligence signboard, characterized in that: include: Sensors deployed on signboards collect environmental data in real time, and wireless network technology is used to collect tourism information within a preset range in real time; Using artificial intelligence algorithms to analyze the real-time environmental data, combining historical data to predict the best route and travel mode within a preset time period, and generating data analysis results; Analyze the tourism information through NLP, generate decision information based on the data analysis results, and automatically generate dynamic display content based on the decision information; An execution instruction is generated based on the display content to control the signboard to display information, and the display content is automatically updated according to the new environmental data and the tourism information.

2. The control method based on artificial intelligence signboard according to claim 1 is characterized in that: The sensors deployed by the signboards collect environmental data in real time, and use wireless network technology to collect tourism information within a preset range in real time, including: Starting the sign system and performing self-check and initialization, obtaining real-time weather information through the sensor, and obtaining weather warning information from an interface of an external meteorological data source; The location information of the sign is obtained through GPS, and the traffic flow and pedestrian density information in front of the sign is obtained using a camera; The sensor data of different types are fused using Kalman filtering to obtain fused sensor data. The Kalman filtering formula is as follows: x′ k =x′ k-1 +K k (z k -Hx′ k-1 ) P k =(I-K k H)P k-1 K k =P k-1 H T (HP k-1 H T +R) -1 In the formula, x′ k is the state estimate at the current moment, x′ k-1 is the state estimate of the previous moment, K k is the Kalman gain, P k is the covariance matrix, P k-1 is the covariance matrix of the previous moment, I is the identity matrix, z k is the observation value, H is the observation matrix, and R is the observation noise; Using edge computing technology to perform real-time processing and preliminary analysis on the sensor data to obtain the environmental data; Based on the location information of the signboard, the tourism information within a preset range is collected in real time using wireless network technology.

3. The control method based on artificial intelligence signboard according to claim 2 is characterized in that: The artificial intelligence algorithm is used to analyze the real-time environmental data, and the best route and travel mode within a preset time period are predicted in combination with historical data, including: Using LSTM to analyze the environmental data and the historical data to capture the long-term dependency between the environmental data; Analyze the environmental data using a deep Q network, learn the long-term dependencies between the environmental data, and find the optimal route and travel mode within a preset time period; Dynamic path optimization is performed according to the real-time environmental data through the A* algorithm combined with the Dijkstra algorithm, and the GA algorithm is used to adjust the optimal route and the travel mode.

4. The control method based on artificial intelligence signboard according to claim 3 is characterized in that: The analyzing the tourism information by NLP, generating decision information in combination with the data analysis result, and automatically generating dynamic display content based on the decision information include: Using the SpaCy library to identify tourism-related entity information from the tourism information; Based on the entity information, BERT is used in combination with sentiment analysis to extract contextual content from the travel information and generate text with sentiment features; The output g based on BERT i Represented as the hidden state of each token, it is used to determine the sentiment type of the travel information: SentimentScore=Softmax(W sent g i +b sent ) Where W sent is the weight matrix of sentiment classification, b sent is a bias term, and the output Softmax value represents the probability of the emotion category; Optimizing the optimal route and the travel mode by combining the text with emotional features through a multi-objective optimization algorithm to generate travel suggestions; Generate the decision information in multiple languages ​​through NLP according to the travel suggestion and the data analysis result; The Tableau tool is integrated to display the decision information in the form of charts and maps to obtain dynamic display content.

5. The control method based on artificial intelligence signboard according to claim 4 is characterized in that: The generating an execution instruction based on the display content to control the sign to display information includes: Generate the execution instruction using a rule-based decision engine according to the display content, and send the execution instruction to the signboard via the MQTT protocol; Using WebSocket technology to maintain a real-time connection with the signboard and transmit the execution instructions and update content in real time; Furthermore, the generation and updating of the display content can be remotely managed and updated in real time through a cloud server.

6. The control method based on artificial intelligence signboard according to claim 5 is characterized in that: The method also captures tourists' feedback information from external systems through the network, and connects with the tourist attraction management platform in real time to obtain tourist flow, scenic spot scheduling and emergency warning information, and integrates and supplements the tourist information.

7. Ice and snow tourism sign, characterized by: include: Environmental perception module, used to collect environmental data and tourism information around the sign; A data processing module, for analyzing the environmental data and the tourism information using an artificial intelligence algorithm, performing route planning and travel mode selection, and generating dynamic multilingual display content; An information display module, used to display the dynamic display content; The network communication module is used to exchange data with the cloud server and the tourist attraction management platform, and dynamically adjust the tourist information and the display content.

8. The ice and snow tourism signboard according to claim 7, characterized in that: The information display module is a high-brightness LED screen that displays the display content through graphics and maps. The network communication module uses wireless communication technology to seamlessly connect with the cloud server and the tourist attraction management platform to achieve multi-party data sharing and real-time updating.

9. The ice and snow tourism signboard according to claim 8, characterized in that: The signboard is designed to be cold-resistant, snow-resistant, waterproof and frost-proof, and has an integrated emergency help function, which automatically contacts management personnel or rescue teams and provides tourists with current location information and emergency situations.

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